{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_3000 = pd.read_csv('./train_3000_avg_pred.csv')\n",
    "pred_33465 = pd.read_csv('./train_33465_avg_pred.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'pred_33465')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#\n",
    "plt.figure(figsize=(20,10))\n",
    "plt.subplot(121)\n",
    "plt.plot(pred_3000.id, pred_3000.score)\n",
    "plt.title('pred_3000')\n",
    "plt.subplot(122)\n",
    "plt.plot(pred_33465.id, pred_33465.score)\n",
    "plt.title('pred_33465')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f36747656d8>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "w1, w2 = 0.3, 0.7\n",
    "plt.figure(figsize=(20,10))\n",
    "plt.subplot(121)\n",
    "sns.distplot(pred_3000.score)\n",
    "sns.distplot(pred_33465.score)\n",
    "plt.legend(['pred_3000','pred_33465'])\n",
    "plt.subplot(122)\n",
    "sns.distplot(w1*pred_3000.score + w2*pred_33465.score)\n",
    "plt.legend(['combine'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "com_score = w1*pred_3000.score + w2*pred_33465.score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_all = pred_3000[['id']].copy()\n",
    "pred_all['label'] = com_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>33466</td>\n",
       "      <td>0.150229</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>33467</td>\n",
       "      <td>0.191778</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>33468</td>\n",
       "      <td>0.166658</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33469</td>\n",
       "      <td>0.162382</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>33470</td>\n",
       "      <td>0.166416</td>\n",
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       "      <th>5</th>\n",
       "      <td>33471</td>\n",
       "      <td>0.149783</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>33472</td>\n",
       "      <td>0.216201</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>33473</td>\n",
       "      <td>0.101080</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>33474</td>\n",
       "      <td>0.218279</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>33475</td>\n",
       "      <td>0.151219</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>33476</td>\n",
       "      <td>0.152258</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>33477</td>\n",
       "      <td>0.244734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>33478</td>\n",
       "      <td>0.168049</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>33479</td>\n",
       "      <td>0.228676</td>\n",
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       "      <th>14</th>\n",
       "      <td>33480</td>\n",
       "      <td>0.262015</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>33481</td>\n",
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       "      <th>16</th>\n",
       "      <td>33482</td>\n",
       "      <td>0.304823</td>\n",
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       "      <th>17</th>\n",
       "      <td>33483</td>\n",
       "      <td>0.168661</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>33484</td>\n",
       "      <td>0.216872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>33485</td>\n",
       "      <td>0.180360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>33486</td>\n",
       "      <td>0.177160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>33487</td>\n",
       "      <td>0.160818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>33488</td>\n",
       "      <td>0.163985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>33489</td>\n",
       "      <td>0.222782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>33490</td>\n",
       "      <td>0.218517</td>\n",
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       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>33491</td>\n",
       "      <td>0.197483</td>\n",
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       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>33492</td>\n",
       "      <td>0.334976</td>\n",
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       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>33493</td>\n",
       "      <td>0.194268</td>\n",
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       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>33494</td>\n",
       "      <td>0.152912</td>\n",
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       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>33495</td>\n",
       "      <td>0.122471</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>66505</th>\n",
       "      <td>99971</td>\n",
       "      <td>0.247267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66506</th>\n",
       "      <td>99972</td>\n",
       "      <td>0.188957</td>\n",
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       "    <tr>\n",
       "      <th>66507</th>\n",
       "      <td>99973</td>\n",
       "      <td>0.165966</td>\n",
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       "    <tr>\n",
       "      <th>66508</th>\n",
       "      <td>99974</td>\n",
       "      <td>0.153998</td>\n",
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       "    <tr>\n",
       "      <th>66509</th>\n",
       "      <td>99975</td>\n",
       "      <td>0.186248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66510</th>\n",
       "      <td>99976</td>\n",
       "      <td>0.273795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66511</th>\n",
       "      <td>99977</td>\n",
       "      <td>0.125860</td>\n",
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       "    <tr>\n",
       "      <th>66512</th>\n",
       "      <td>99978</td>\n",
       "      <td>0.177428</td>\n",
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       "    <tr>\n",
       "      <th>66513</th>\n",
       "      <td>99979</td>\n",
       "      <td>0.140164</td>\n",
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       "    <tr>\n",
       "      <th>66514</th>\n",
       "      <td>99980</td>\n",
       "      <td>0.200889</td>\n",
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       "    <tr>\n",
       "      <th>66515</th>\n",
       "      <td>99981</td>\n",
       "      <td>0.188050</td>\n",
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       "    <tr>\n",
       "      <th>66516</th>\n",
       "      <td>99982</td>\n",
       "      <td>0.180666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66517</th>\n",
       "      <td>99983</td>\n",
       "      <td>0.120400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66518</th>\n",
       "      <td>99984</td>\n",
       "      <td>0.175411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66519</th>\n",
       "      <td>99985</td>\n",
       "      <td>0.156292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66520</th>\n",
       "      <td>99986</td>\n",
       "      <td>0.205980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66521</th>\n",
       "      <td>99987</td>\n",
       "      <td>0.166794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66522</th>\n",
       "      <td>99988</td>\n",
       "      <td>0.122893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66523</th>\n",
       "      <td>99989</td>\n",
       "      <td>0.179049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66524</th>\n",
       "      <td>99990</td>\n",
       "      <td>0.236850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66525</th>\n",
       "      <td>99991</td>\n",
       "      <td>0.210551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66526</th>\n",
       "      <td>99992</td>\n",
       "      <td>0.231780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66527</th>\n",
       "      <td>99993</td>\n",
       "      <td>0.193692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66528</th>\n",
       "      <td>99994</td>\n",
       "      <td>0.203373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66529</th>\n",
       "      <td>99995</td>\n",
       "      <td>0.147682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66530</th>\n",
       "      <td>99996</td>\n",
       "      <td>0.112549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66531</th>\n",
       "      <td>99997</td>\n",
       "      <td>0.148992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66532</th>\n",
       "      <td>99998</td>\n",
       "      <td>0.184344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66533</th>\n",
       "      <td>99999</td>\n",
       "      <td>0.215345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66534</th>\n",
       "      <td>100000</td>\n",
       "      <td>0.226725</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66535 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           id     label\n",
       "0       33466  0.150229\n",
       "1       33467  0.191778\n",
       "2       33468  0.166658\n",
       "3       33469  0.162382\n",
       "4       33470  0.166416\n",
       "5       33471  0.149783\n",
       "6       33472  0.216201\n",
       "7       33473  0.101080\n",
       "8       33474  0.218279\n",
       "9       33475  0.151219\n",
       "10      33476  0.152258\n",
       "11      33477  0.244734\n",
       "12      33478  0.168049\n",
       "13      33479  0.228676\n",
       "14      33480  0.262015\n",
       "15      33481  0.141301\n",
       "16      33482  0.304823\n",
       "17      33483  0.168661\n",
       "18      33484  0.216872\n",
       "19      33485  0.180360\n",
       "20      33486  0.177160\n",
       "21      33487  0.160818\n",
       "22      33488  0.163985\n",
       "23      33489  0.222782\n",
       "24      33490  0.218517\n",
       "25      33491  0.197483\n",
       "26      33492  0.334976\n",
       "27      33493  0.194268\n",
       "28      33494  0.152912\n",
       "29      33495  0.122471\n",
       "...       ...       ...\n",
       "66505   99971  0.247267\n",
       "66506   99972  0.188957\n",
       "66507   99973  0.165966\n",
       "66508   99974  0.153998\n",
       "66509   99975  0.186248\n",
       "66510   99976  0.273795\n",
       "66511   99977  0.125860\n",
       "66512   99978  0.177428\n",
       "66513   99979  0.140164\n",
       "66514   99980  0.200889\n",
       "66515   99981  0.188050\n",
       "66516   99982  0.180666\n",
       "66517   99983  0.120400\n",
       "66518   99984  0.175411\n",
       "66519   99985  0.156292\n",
       "66520   99986  0.205980\n",
       "66521   99987  0.166794\n",
       "66522   99988  0.122893\n",
       "66523   99989  0.179049\n",
       "66524   99990  0.236850\n",
       "66525   99991  0.210551\n",
       "66526   99992  0.231780\n",
       "66527   99993  0.193692\n",
       "66528   99994  0.203373\n",
       "66529   99995  0.147682\n",
       "66530   99996  0.112549\n",
       "66531   99997  0.148992\n",
       "66532   99998  0.184344\n",
       "66533   99999  0.215345\n",
       "66534  100000  0.226725\n",
       "\n",
       "[66535 rows x 2 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "upper = np.percentile(com_score,90)\n",
    "downer = np.percentile(com_score,10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_all.loc[(pred_all.label>upper).values,'label']=1\n",
    "pred_all.loc[(pred_all.label<downer).values,'label']=0\n",
    "filter = (pred_all.label>upper)|(pred_all.label<downer)\n",
    "pred_selec= pred_all.iloc[filter.values]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_selec = pred_selec.astype({'label':np.int64})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "unlabel_y = pred_selec.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "unlabel_y.to_csv('unlabel_y.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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